Forest biomass or above-ground carbon stock is the mass of carbon that stored in trees which requires a continuous monitoring in order to predict the amount of potential carbon accumulation of the forest. Therefore, the forest has an important role at absorbing carbon Dioxide (CO2) from the atmosphere. This research aims to measure the capability of Quick Terrain Modeller software at estimating above-ground carbon stock by single tree segmentation combining ground inventory, Light Detection and Ranging (LiDAR), and by using allometric equations. In particular, to achieve the aim, there are three (3) objectives were outlined. Canopy Height Models (CHM) was generated via Quick Terrain Modeller (QTM) and ArcGIS. Non-linear Regression analyses were performed for both surface models to ensure the models were fit to estimate carbon stock. Secondly, tree contours were delineated using watershed transformation. Local maxima were determined at the raster as a pour point for watershed and also represent the highest peak of the tree crown. In addition, flow direction, drop output, and flow accumulation of the raster were also determined to generate contour from the watershed transformation. Manual tree crown projection was performed by watershed tree contour to generate Crown Projection Area (CPA). Then, from the digitized CPA, carbon stock and above-ground biomass was calculated using equations from [1] and [2]. Thirdly, tree species on the selected area were extracted and finally a map of tree carbon stock by species was produced. From the generated map, total carbon stock according to species and total carbon stock in single tree according to species information were extracted. As a result, Hopea sulcata; the endangered tree species appeared to be the highest appearance in the map followed by Dipterocarpus verrucosus, Shorea macroptera, Endospermum diadenum, and the other less appeal species. Also from the map, Hopea Sulcata has the highest carbon stock which is 23% compared to the other species. However, for a single tree, Dipterocarpus verrucosus held the highest carbon stock which is 1565.401 kg/tree.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.